Dr. SUDHARANI
Asst professor
CSE
KL UNIVERSITY
16 YEARS
DBMS, ARTIFICIAL INTELLIGENCE, MACHINE LEARNING
DEEP LEARNING
Mail: v.sudharani@sru.edu.in
Asst professor
CSE
KL UNIVERSITY
16 YEARS
DBMS, ARTIFICIAL INTELLIGENCE, MACHINE LEARNING
DEEP LEARNING
Mail: v.sudharani@sru.edu.in
P.hd
M.Tech cse
MCA
Ph.D
UG
M. A. Shaik, V. S. Rani, A. Fatima, M. Parveen, J. Juwairiyyah and N. Fatima, "Secure Data Exchange in Cloud Computing: Enhancing Confidentiality, Integrity, and Availability Through Data Partitioning and Encryption," 2024 International Conference on Smart Technologies for Sustainable Development Goals (ICSTSDG), Chennai - 600077, Tamil Nadu, India, 2024, pp. 1-6, doi: 10.1109/ICSTSDG61998.2024.11026651. keywords: {Ciphers;Cloud computing security;Simulated annealing;Machine learning;Organizations;Real-time systems;Encryption;Partitioning algorithms;Sustainable development;Genetic algorithms;cloud security;annealing;secure data exchange;optimized block ciphers;encryption},
Vupulluri, S.R.; Munagala, J.K. Histopathological Image Analysis Using Deep Learning Framework. Eng. Proc. 2023, 59, 132. https://doi.org/10.3390/engproc2023059132
Rani V, S. ., & Kumar, M. J. . (2022). Histopathological Image Classification Methods and Techniques in Deep Learning Field. International Journal on Recent and Innovation Trends in Computing and Communication, 10(2s), 158–165. https://doi.org/10.17762/ijritcc.v10i2s.5923
The following are the findings of this study on the classification of breast cancer histopathology images: Using classic machine learning approaches for histopathological image classification in breast cancer detection requires pathologists with professional clinical expertise, and the feature extraction procedure takes a long time and energy. The typical use of machine learning for histopathological image categorization in breast cancer detection is seriously harmed. Deep learning can automatically learn fetures